From 925087356b853e2099c1b60d8b757d7aa02121a9 Mon Sep 17 00:00:00 2001
From: Chris Dyer <cdyer@cab.ark.cs.cmu.edu>
Date: Tue, 2 Oct 2012 00:19:43 -0400
Subject: cdec cleanup, remove bayesian stuff, parsing stuff

---
 rst_parser/arc_factored.cc | 151 ---------------------------------------------
 1 file changed, 151 deletions(-)
 delete mode 100644 rst_parser/arc_factored.cc

(limited to 'rst_parser/arc_factored.cc')

diff --git a/rst_parser/arc_factored.cc b/rst_parser/arc_factored.cc
deleted file mode 100644
index 74bf7516..00000000
--- a/rst_parser/arc_factored.cc
+++ /dev/null
@@ -1,151 +0,0 @@
-#include "arc_factored.h"
-
-#include <set>
-#include <tr1/unordered_set>
-
-#include <boost/pending/disjoint_sets.hpp>
-#include <boost/functional/hash.hpp>
-
-#include "arc_ff.h"
-
-using namespace std;
-using namespace std::tr1;
-using namespace boost;
-
-void EdgeSubset::ExtractFeatures(const TaggedSentence& sentence,
-                                 const ArcFeatureFunctions& ffs,
-                                 SparseVector<double>* features) const {
-  SparseVector<weight_t> efmap;
-  for (int j = 0; j < h_m_pairs.size(); ++j) {
-    efmap.clear();
-    ffs.EdgeFeatures(sentence, h_m_pairs[j].first,
-                     h_m_pairs[j].second,
-                     &efmap);
-    (*features) += efmap;
-  }
-  for (int j = 0; j < roots.size(); ++j) {
-    efmap.clear();
-    ffs.EdgeFeatures(sentence, -1, roots[j], &efmap);
-    (*features) += efmap;
-  }
-}
-
-void ArcFactoredForest::ExtractFeatures(const TaggedSentence& sentence,
-                                        const ArcFeatureFunctions& ffs) {
-  for (int m = 0; m < num_words_; ++m) {
-    for (int h = 0; h < num_words_; ++h) {
-      ffs.EdgeFeatures(sentence, h, m, &edges_(h,m).features);
-    }
-    ffs.EdgeFeatures(sentence, -1, m, &root_edges_[m].features);
-  }
-}
-
-void ArcFactoredForest::PickBestParentForEachWord(EdgeSubset* st) const {
-  for (int m = 0; m < num_words_; ++m) {
-    int best_head = -2;
-    prob_t best_score;
-    for (int h = -1; h < num_words_; ++h) {
-      const Edge& edge = (*this)(h,m);
-      if (best_head < -1 || edge.edge_prob > best_score) {
-        best_score = edge.edge_prob;
-        best_head = h;
-      }
-    }
-    assert(best_head >= -1);
-    if (best_head >= 0)
-      st->h_m_pairs.push_back(make_pair<short,short>(best_head, m));
-    else
-      st->roots.push_back(m);
-  }
-}
-
-struct WeightedEdge {
-  WeightedEdge() : h(), m(), weight() {}
-  WeightedEdge(short hh, short mm, float w) : h(hh), m(mm), weight(w) {}
-  short h, m;
-  float weight;
-  inline bool operator==(const WeightedEdge& o) const {
-    return h == o.h && m == o.m && weight == o.weight;
-  }
-  inline bool operator!=(const WeightedEdge& o) const {
-    return h != o.h || m != o.m || weight != o.weight;
-  }
-};
-inline bool operator<(const WeightedEdge& l, const WeightedEdge& o) { return l.weight < o.weight; }
-inline size_t hash_value(const WeightedEdge& e) { return reinterpret_cast<const size_t&>(e); }
-
-
-struct PriorityQueue {
-  void push(const WeightedEdge& e) {}
-  const WeightedEdge& top() const {
-    static WeightedEdge w(1,2,3);
-    return w;
-  }
-  void pop() {}
-  void increment_all(float p) {}
-};
-
-// based on Trajan 1977
-void ArcFactoredForest::MaximumSpanningTree(EdgeSubset* st) const {
-  typedef disjoint_sets_with_storage<identity_property_map, identity_property_map,
-      find_with_full_path_compression> DisjointSet;
-  DisjointSet strongly(num_words_ + 1);
-  DisjointSet weakly(num_words_ + 1);
-  set<unsigned> roots, rset;
-  unordered_set<WeightedEdge, boost::hash<WeightedEdge> > h;
-  vector<PriorityQueue> qs(num_words_ + 1);
-  vector<WeightedEdge> enter(num_words_ + 1);
-  vector<unsigned> mins(num_words_ + 1);
-  const WeightedEdge kDUMMY(0,0,0.0f);
-  for (unsigned i = 0; i <= num_words_; ++i) {
-    if (i > 0) {
-      // I(i) incidence on i -- all incoming edges
-      for (unsigned j = 0; j <= num_words_; ++j) {
-        qs[i].push(WeightedEdge(j, i, Weight(j,i)));
-      }
-    }
-    strongly.make_set(i);
-    weakly.make_set(i);
-    roots.insert(i);
-    enter[i] = kDUMMY;
-    mins[i] = i;
-  }
-  while(!roots.empty()) {
-    set<unsigned>::iterator it = roots.begin();
-    const unsigned k = *it;
-    roots.erase(it);
-    cerr << "k=" << k << endl;
-    WeightedEdge ij = qs[k].top();  // MAX(k)
-    qs[k].pop();
-    if (ij.weight <= 0) {
-      rset.insert(k);
-    } else {
-      if (strongly.find_set(ij.h) == k) {
-        roots.insert(k);
-      } else {
-        h.insert(ij);
-        if (weakly.find_set(ij.h) != weakly.find_set(ij.m)) {
-          weakly.union_set(ij.h, ij.m);
-          enter[k] = ij;
-        } else {
-          unsigned vertex = 0;
-          float val = 99999999999;
-          WeightedEdge xy = ij;
-          while(xy != kDUMMY) {
-            if (xy.weight < val) {
-              val = xy.weight;
-              vertex = strongly.find_set(xy.m);
-            }
-            xy = enter[strongly.find_set(xy.h)];
-          }
-          qs[k].increment_all(val - ij.weight);
-          mins[k] = mins[vertex];
-          xy = enter[strongly.find_set(ij.h)];
-          while (xy != kDUMMY) {
-          }
-        }
-      }
-    }
-  }
-}
-
-- 
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